Fitting of Parametric Space Curves and Surfaces by Using the Geometric Error Measure

摘要: For pattern recognition and computer vision, fitting of curves surfaces to a set given data points in space is relevant subject. In this paper, we review the current orthogonal distance algorithms for parametric model features, and, present two new well organized easily understandable manner. Each these estimates parameters which minimize square sum shortest error distances between feature points. The are grouped simultaneously estimated terms form, position, rotation parameters. We give various examples point space.